How to choose the activation function in neuroevolution?
When it comes to genetic algorithms (neuroevolution), you can pretty much evolve any kind of parameters. You just need to have a fairly complex system where each parameter changes the way the inputs are affecting the outputs.

So, to answer your question, any activation function should work! It would be surprising that the activation function is your problem. But if you want to test some activation functions, here's a list of activation functions. But tanh should work perfectly fine.

As I already mentioned in another answer, the key to have a great neuroevolution algorithm is the fitness function. Your rewards should reflect the goal you're aiming for. You didn't mentioned what fitness function you used, but here's what I suggest: reward a player ONLY if he progresses in the game. For example, your fitness function could simply be the distance traveled by your birds. This could maybe solve your problem...